With the advancement of Machine Learning, since its beginning and over the last years, a special attention has been given to the\nArtificial Neural Network. As an inspiration from natural selection of animal groups and humanâ??s neural system, the Artificial\nNeural Network also known as Neural Networks has become the new computational power which is used for solving real world\nproblems. NeuralNetworks alone as a concept involve various methods for achieving their success; thus, this reviewpaper describes\nan overview of such methods called Particle Swarm Optimization, Backpropagation, and Neural Network itself, respectively. A\nbrief explanation of the concepts, history, performances, advantages, and disadvantages is given, followed by the latest researches\ndone on these methods. A description of solutions and applications on various industrial sectors such asMedicine or Information\nTechnology has been provided. The last part briefly discusses the directions, current, and future challenges of Neural Networks\ntowards achieving the highest success rate in solving real world problems.
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